Mercurial > repos > proteomisc > preprocess_dataset
diff preprocess_datasets/Affymetrix_Preprocessing.R @ 41:8aaf6fdb06d6 draft
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author | proteomisc |
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date | Sat, 16 Dec 2023 12:30:14 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/preprocess_datasets/Affymetrix_Preprocessing.R Sat Dec 16 12:30:14 2023 +0000 @@ -0,0 +1,91 @@ +options(show.error.messages=F,warn=-1, error=function(){cat(geterrmessage(),file=stderr());q("no",1,F)}) +sink(stdout(), type = "message") +sink(stdout() ,type = "output") +suppressWarnings(suppressMessages(library(affy))) +suppressWarnings(suppressMessages(library(affyPLM))) +suppressWarnings(suppressMessages(library(batch))) +suppressWarnings(suppressMessages(library(annotate))) +suppressWarnings(suppressMessages(library(limma))) +suppressWarnings(suppressMessages(library(markdown))) +suppressWarnings(suppressMessages(library(knitr))) +source_local <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +file_path <- function(fname){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + pato <- paste(base_dir, fname, sep="/") + return(pato) +} +base_dir <- function(){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + return(base_dir) +} +source_local("Affymetrix_Preprocessing_Functions.R") +listArguments = parseCommandArgs(evaluate=FALSE) +thefunctions=listArguments[["thefunctions"]] +listArguments[["thefunctions"]]=NULL +h=listArguments[["h"]] +listArguments[["h"]]=NULL +w=listArguments[["w"]] +listArguments[["w"]]=NULL +if (!is.null(listArguments[["image"]])){ + load(listArguments[["image"]]) + listArguments[["image"]]=NULL +} +listArguments[["rawdata"]]=MicroArray_Object$affy_object +if(datasetsource=="intern"){ +designo<-MicroArray_Object$designo +} + +if(datasetsource=="extern"){ +listArguments<-append(listArguments,list(datasetsource=datasetsource,listfullnames=listfullnames)) +} +Prepro_object<-do.call(thefunctions,listArguments) +if(datasetsource=="extern"){ +rownames(Prepro_object$data.bg@phenoData@data)<-listfullnames +colnames(exprs(Prepro_object$data.bg))<-listfullnames +colnames(exprs(Prepro_object$data.sm))<-listfullnames +colnames(exprs(Prepro_object$data.norm))<-listfullnames +colnames(exprs(Prepro_object$data.bg))<-listfullnames +colnames(exprs(Prepro_object$data.norm))<-listfullnames +rownames(Prepro_object$data.norm@phenoData@data)<-listfullnames +rownames(Prepro_object$data.norm@protocolData@data)<-listfullnames +} + +png(filename ="boxplot_before_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.bg)))), main="Boxplot of intensities before Normalization",col="red",las=2,mar=c(15,2,1,1)) +invisible(dev.off()) + +png(filename ="boxplot_after_NM.png",width = w, height = h, units = "px", pointsize = 14, bg = "white") +boxplot((na.omit(as.data.frame(exprs(Prepro_object$data.sm)))), main="Boxplot of intensities After Normalization",col="red",ylab="(intensities)",las=2,mar=c(15,2,1,1)) +invisible(dev.off()) + +png(filename ="MA_plot.png",width = w, height = h) +MAplot((Prepro_object$data.norm) , + show.statistics = F, span = 2/3, family.loess = "gaussian", + cex = 2, plot.method = as.character("smoothScatter"), + azdd.loess = TRUE, lwd = 1, lty = 1, loess.col = "red") + +invisible(dev.off()) + +png(filename = "densities_plot_before_NM.png",width = w, height = h) +plotDensities(exprs(Prepro_object$data.bg),log=T) +invisible(dev.off()) + +png(filename = "densities_plot_after_NM.png",width = w, height = h) +plotDensities(exprs(Prepro_object$data.norm),log=T) +invisible(dev.off()) + +AffymetrixRmd=file_path("Affymetrix.Rmd") +Style=file_path("look.css") +suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T))) +#suppressWarnings(suppressMessages(markdownToHTML(AffymetrixRmd,output="PreprocessingPlots.html", stylesheet=Style))) +#suppressWarnings(suppressMessages(knit2html(AffymetrixRmd,output="PreprocessingPlots.html",quiet = T))) +rm(listArguments) +save.image("MicroArray.Preprocessing.RData") +sink() +sink()